Protein Folding Using Quantum Topology

How to describe protein backbone using Ramachandran angles? What are alpha helixes and beta sheets? How can we predict protein structure using quantum field theory? Professor of Mathematics Jørgen Andersen answers these tricky questions.

One of the contemporary big problems in molecular biology is to understand the folding of macromolecules like DNA, RNA, and proteins. The basic problem is that you’re given a word with a number of letters and there it depends on whether we’re talking about RNA, DNA or proteins. For RNA and DNA it’s four letters, and for proteins it’s twenty letters. But the point is that you’re given this word in these letters and what you want from there is to predict the global three-dimensional structure that this macromolecule folds into. That’s been a problem for about 30 years in the field.

There are various clusters that are strongly correlated with the known motifs. So, for example, there is what we call the alpha cluster which has to do with alpha helixes, there is couple of beta clusters that have to do with standard beta motifs, but there are lots of other clusters which correspond to interesting new motifs.

There are about 2000 local patterns that we’ve seen popping out now and we are trying to understand what is the correlation between the primary sequence of these patterns. Some of them have a clear significance. We’re trying to devise energy contributions for each of such patterns and then trying to see if we can create algorithms that generate all structures with a certain sequence of patterns. And this is a combinatorial problem that we’ve actually solved very recently.